Why edge computing changes the game for businesses

The industry transitioned from data silos to cloud computing, which allowed businesses to push data off-site and into data centers that provided a centralized architecture. This data was used to make decisions, analyzed for trending and anomalies, and provided information back to the business or government agency to support improvements, efficiencies, quality control, and customer delivery.

The transition to distributed architectures

Today, we transition into a distributed architecture for the purposes of reaching real-time intelligence. With this new era, new technologies and architectures introduce smarter ways to collect, store, and analyze data closer to the end-point device, asset, and building (on-premise). This is essentially processing the data as close to the source of the data as possible. The edge can be anything other than the central cloud or data center, and thus that is why there are varying definitions being shared with the enterprise.

Assets can be fixed or mobile (moving) and even multi-modal (more than one way it is being transported or moved). Related technologies that augment or come together to support in this real-time intelligence and business automation include edge computing, artificial intelligence (AI), machine learning, and other Internet of Things (IoT)-related technologies. Real-time intelligence is important as faster processing and data analytics feedback can support in responding and making decisions around failures, maintenance, repairs, tracking, monitoring, theft, breaches, production, and other important business operations.

Why is this game-changing for businesses and government?

This is game-changing as businesses push further into both digital transformation of their operations and require greater automation to offset the need for workers to do mundane and repetitive tasks. Industry 4.0 (including Industry 5.0) is also a driver as we push the limits on human and machine collaboration ranging from robotics to robotic process automation. For example, businesses can look at the back-office (operational, production, manufacturing) and front-office (sales, marketing, customer service) and determine what areas of their business and processes would benefit from real-time intelligence. Real-time intelligence is essentially using data to make faster decisions.

Some of the primary business benefits of edge computing based on recent survey research from BusinessEdgeReport.com include:

• Lower latency
• Faster distributed application performance
• Local data capture, store, and processing
• Scalability and elasticity

Businesses today are faced with a several major challenges including a lack of skilled and knowledge workers, hybrid or work-from-home workforces (fewer people in the office or building), and uncertainty in the economy and pandemic impact. These challenges further drive the need to look to machines and automation to support operations. Businesses that have operations in remote locations where the monitoring and tracking of assets are vital to the business will rely even more on robotics and IoT sensor systems to remove the human element for specific job functions.

For cities, this may mean departments and agencies will seek the support of smart cameras, digital signage, and intelligent transportation systems to provide better and safer city services. Some of these core automation and IoT solutions are not possible without edge computing, and if anything solutions are made possible through a combination of architectures depending on the data actions required. Businesses will need to evaluate their existing architecture, and some may move to hybrid architectures which are a combination of both cloud and edge computing.

The bottom line for enterprises is edge computing provides real-time intelligence to advance digital transformation journeys. Companies of all sizes continue to explore and adopt technologies to augment, support, and provide benefits for the workforce, operations, or customer services. Edge computing removes barriers, shortens time-frames, and provides solutions for actionable business decision-making.

About the author

Stephanie Atkinson is CEO and founder of Compass Intelligence, a provider of market research and consulting services for global companies in the telecom, mobility, IoT, and IT industries.

DISCLAIMER: Guest posts are submitted content. The views expressed in this post are that of the author, and don’t necessarily reflect the views of Edge Industry Review (EdgeIR.com).

Article Topics

Compass Intelligence  |  digital transformation  |  edge computing  |  IoT  |  market research